3 accepted papers
Extracting insights from text columns can bechallenging and time-intensive. Existing methods for topic modeling and feature extractionare based on syntactic features and often overlook the semantics. We introduce the semantictext column featurization problem, and presenta scalable approach for autom…
The popularity of Large Language Models (LLMs) have unleashed a new age of Language Agents for solving a diverse range of tasks. While contemporary frontier LLMs are capable enough to power reasonably good Language agents, the closed-API model makes it hard to improve in cases they perform sub-optim…
Target similarity tuning (TST) is a method of selecting relevant examples in natural language (NL) to code generation through large language models (LLMs) to improve performance. Its goal is to adapt a sentence embedding model to have the similarity between two NL inputs match the similarity between…